On the real estate market efficiency

This reseach reexamines the efficiency hypothesis of the real estate market using monthly data and the vector autoregressive (VAR) modelling technique. The tests focus on the causal linkage between real estate returns and a number of relevant financial and economic variables. An eight-by-eight VAR model is estimated using the FPE and the specific gravity criteria, in conjunction with an extensive series of specification tests. The empirical results distilled from system estimations suggest that the real estate market is efficient with respect to available information on the industrial production, the risk premia, the term structure of interest rates, and the monetary base. Movements in these variables are quickly and fully utilized by market agents, perhaps owing to the intensity with which their relationship with stock returns has been discussed in the literature and the popular media. However, the results also suggest the presence of a significant lagged relationship between real estate returns and fiscal policy moves, even when the paths through other potential determinants of these returns are taken into account. Of course, our finding that the fiscal policy measure is useful in predicting stock returns does not necessarily imply that the real estate market is inefficient. At a minimum, inefficiency is revealed only if a careful analysis of the budgetary process can help design a profitable (exploitable) trading strategy.     

The predictability of real estate returns and market timing

Recent evidence suggests that all asset returns are predictable to some extent with excess returns on real estate relatively easier to forecast. This raises the issue of whether we can successfully exploit this level of predictability using various market timing strategies to realize superior performance over a buy-and-hold strategy. We find that the level of predicability associated with real estate leads to moderate success in market timing, although this is not necessarily the case for the other asset classes examined in general. Besides this, real estate stocks typically have higher trading profits and higher mean risk-adjusted excess returns when compared to small stocks as well as large stocks and bonds even though most real estate stocks are small stocks.     

Is there a real estate factor premium?

In this paper, we study the variation of expected returns on five different asset portfolios in a multi-factor model. We found the presence of a real estate factor, in addition to both a stock factor and a bond factor in asset pricing. This suggests that mutual fund managers should seriously consider including real estate assets in their portfolios, since one cannot capture the real estate factor premium without having some kind of real estate exposure. Another result is that the market segmentation found in previous studies disappears in a more general model of asset pricing in which we allow for multi-factors other than the market factor to affect asset returns. This implies that real estate assets can be treated just like other assets as far as mean-variance efficient asset allocations are concerned. We also have some preliminary evidence that equity REITs and the Russell-NCREIF index are driven by the same underlying real estate factor.     

Bank risk and real estate: An asset pricing perspective

While a number of papers have investigated the time-series behavior ofex post bank stock returns and real estate returns, no study has comprehensively studied the relationship betweenex ante risk premiums on both assetsand the time-varying nature of such premiums in relationship to economic and real estate market conditions. In this study, we investigate how the changing nature of bank risk taking, especially in the real estate market, has affected theex ante pricing of risk in the market for bank stocks. We find that the time variation in bank risk premiums are partly determined by interest rate and real estate market conditions. We also discover that the real estate factor has been important for banks in the 1980s.     

The sensitivity of bank stock returns to real estate

According to the Federal Reserve Board, banking firms have recently been shifting significantly larger portions of their loan portfolios into real estate. This increase in real estate lending has caused concern about the continuing economic health of banks on the part of state and federal regulators, since changes in real estate returns, evidenced by changes in property value, can potentially have a significant impact on bank default risk and profit-ability. However, concerned parties do not seem to have explicitly considered the relationship between mortgage default risk and the specific characteristics of real estate investments.This study examines the sensitivities of stock returns for different bank groups, based on the percentage of total loans in real estate and the percentage of loans in five different mortgage categories (construction and development loans, farmland loans, one- to four-family residential loans, multifamily residential loans, and nonresidential and nonfarm loans), to changes in real estate market returns. This is done by developing and using a three-index model.The results of this study indicate that bank stocks, overall, are very sensitive to changes in real estae returns. Banks, with a larger portion of their total loans invested in all types of real estate loans, except farmland loans, are most sensitive to changes in real estate returns.     

Time-varying correlation between stock market returns and real estate returns

Direct investment in commercial or residential real estate is found to provide valuable diversification benefits for Australian investors though this is not so evident for indirect real estate investment vehicles like listed Australian real estate investment trusts (A-REIT). Further, multivariate analysis of Australian real estate and share market quarterly returns, spanning the period from the 3rd quarter 1986 to the 3rd quarter 2009, suggest that the correlation between real estate returns and share market returns is time-varying. Finally, while all of the asset class correlation coefficients increased with the Global Financial Crisis period this broad movement in asset class correlation is not evident in during the Wall Street Crash of 1987.     

The integration of the real estate market and the stock market: Some preliminary evidence

The current study investigates whether the commercial real estate market is segmented from the stock market using the framework of Jorion and Schwartz (1986). Evidence is found to support the hypothesis that segmentation does exist as the result of indirect barriers such as the cost, amount, and quality of information for real estate rather than legal constraints. However, this evidence is contingent on whether real estate returns are computed with appraised values or imputed sale prices and on which market proxy is chosen.     

Jobs,location, and real estate

The decision to relocate has traditionally been based on job opportunities alone, with no attention paid to the real estate market. The cost of housing, its rate of return, and its specificity to a location do not enter the decision to move or stay. This article develops a more general definition of income, including real estate and labor markets. The null hypothesis is that relocation is based on comparing labor income differentials alone. The alternative is that income is more broadly based, including real estate returns. Estimates are provided in a quantal choice framework.     

The value of control: Evidence from full and partial acquisitions in the real estate industry

We investigate the differential wealth effects of (1) full and partial control acquisitions, (2) nonreal estate, real estate and REIT participants, and (3) single- and multiple-bidder events. We find that target firms earn positive excess returns at the announcement of partial and full acquisitions, but acquisitions that result in control earn larger excess returns than noncontrol acquisitions. An examination of industry differences shows that real estate firms or REITs do not earn higher returns relative to nonreal estate firms. Our analysis of market structure finds that bidders that are not involved in an acquisition program earn greater announcement period returns than prior acquirers. For target firms, we find that those with a single offer earn higher returns than those with subsequent offers. A cross-sectional regression analysis shows that while market structure is important in explaining returns, the main determining factor for target firms is the degree of control sought.     

Risk and return in real estate

Basic information is provided on the returns and risks from 1978 through 1985 for unleveraged equity real estate compared with stocks and bonds. Data sources include the Russell-NCREIF index, the Evaluation Associates index, and the Goldman Sachs equity real estate investment trust index. Findings reveal that the aggregate return for the publicly traded equity real estate investment trust index in nearly twice that of the other real estate series, and more than twice that of the Standard & Poor index. The equity real estate investment trust is far more volatile than the other two real estate series. Neither the Goldman Sachs nor the other two indexes exactly measure the returns or risks on equity real estate. The volatility of the equity real estate investment trust leads it to overstate the risk of this investment category, while the other two indexes are not return indexes. Estimates from this study indicate that real estate risk lies plausibly midway between that of stocks and bonds, in the 9 percent to 13 percent range.